The present invention relates to machine aided writing systems and methods. In particular, the present invention relates to systems and methods for aiding users in writing in non-native languages.
With an ever increasing global economy, and with the rapid development of the Internet, people all over the world are becoming increasingly familiar with writing in a language which is not their native language. Unfortunately, for some societies that possess significantly different cultures and writing styles, the ability to write in some non-native languages is an ever-present barrier. When writing in a non-native language (for example English), language usage mistakes are frequently made by the non-native speakers (for example, people who speak Chinese, Japanese, Korean or other non-English languages). These kind of mistakes can include both grammatical mistakes and improper usage of collocations such as verb-object, adjective-noun, adverb-verb, etc.
Many people have the ability to write in a non-native language using proper grammar, but they still may struggle with mistakes in collocations between two the words. Still others struggle with both grammar and other mistakes such as collocations between two words. While spell checking and grammar checking programs and systems are useful in correcting grammatical mistakes, detection and/or correction of mistakes in collocations between two words can be difficult, particularly since these mistakes can be otherwise grammatically correct. Therefore, grammar checkers typically provide very little assistance, if any, in detecting mistakes relating to the collocation between words. English is used as an example of the non-native language in the following discussion, but these problems persist across other language boundaries.
For example, consider the following sentences which contain collocation mistakes which cause the sentences to not be native-like English, even if otherwise grammatically correct.                1. Open the light.        2. Everybody hates the crowded traffic on weekends.        3. This is a check of US$ 500.        4. I congratulate you for your success.The native-like English versions of these sentences should be like:        1. Turn on the light.        2. Everybody hates the heavy traffic on weekends.        3. This is a check for US$ 500.        4. I congratulate you on your success.        
As an example of the barriers faced by non-native English speaking peoples, consider the plight of the Chinese user. By culture, background and thinking habits, Chinese people often produce English sentences which may be grammatical, but not natural. For example, Chinese people tend to directly translate subjects in Chinese into subjects in English, and do the same with objects and verbs. When writing in English, Chinese people often experience difficulty in deciding the collocations between verbs and prepositions, adjectives and nouns, verbs and nouns, etc. Moreover, in specific domains like the business domain, special writing skills and styles are needed.
Common dictionaries are mainly used by non-native speakers for the purpose of reading (a kind of decoding process), but these dictionaries do not provide enough support for writing (a kind of encoding process). They only provide the explanation of a single word, and they typically do not provide sufficient information to explain relevant phrases and collocations. Moreover, there is no easy way to get this kind of information from dictionaries, even if some of the information is provided in the dictionaries. On the other hand, current widely used grammar checking tools have some limited ability in detecting apt-to-make grammatical mistakes, but are not able to detect the collocation mistakes.
Although the aforementioned problems are described with reference to English language writing by native Chinese speaking people, these problems are common for people who are writing in a first (non-native) language, but who are native speakers of a second (native) language. In light of these problems, a system or method which aids non-native speakers in preparing documents without collocation mistakes would be a significant improvement in the art. Further, an improved method of constructing a collocation mistake pattern or template database, for use by such a system or method would be a significant improvement.